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Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS.
- Source :
-
Abdominal radiology (New York) [Abdom Radiol (NY)] 2024 May; Vol. 49 (5), pp. 1615-1625. Date of Electronic Publication: 2024 Apr 23. - Publication Year :
- 2024
-
Abstract
- Purpose: To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort.<br />Methods: Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WI <subscript>S</subscript> ), standard diffusion-weighted imaging (DWI <subscript>S</subscript> ), fast T2WI with DLR (T2WI <subscript>DL</subscript> ), and fast DWI with DLR (DWI <subscript>DL</subscript> ) were enrolled in this prospective study. Imaging quality was evaluated by measuring signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scoring. Additionally, the apparent diffusion coefficient (ADC) of bladder lesions derived from DWI <subscript>S</subscript> and DWI <subscript>DL</subscript> was measured and VI-RADS scoring was performed. Paired t-test or paired Wilcoxon signed-rank test were performed to compare image quality score, SNR, CNR, and ADC between standard sequences and fast sequences with DLR. The diagnostic performance for VI-RADS was assessed using the area under the receiver operating characteristic curve (AUC).<br />Results: Compared to T2WI <subscript>S</subscript> and DWI <subscript>S</subscript> , T2WI <subscript>DL</subscript> and DWI <subscript>DL</subscript> reduced the acquisition time from 5:57 min to 3:13 min and showed significantly higher SNR, CNR, qualitative image quality score of overall image quality, image sharpness, and lesion conspicuity. There were no significant differences in ADC and AUC of VI-RADS between standard sequences and fast sequences with DLR.<br />Conclusions: The application of DLR to T2WI and DWI reduced examination time and significantly improved image quality, maintaining ADC and the diagnostic performance of VI-RADS for evaluating muscle invasion in bladder cancer.<br /> (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
- Subjects :
- Humans
Prospective Studies
Male
Female
Aged
Middle Aged
Neoplasm Invasiveness diagnostic imaging
Urinary Bladder diagnostic imaging
Aged, 80 and over
Adult
Image Interpretation, Computer-Assisted methods
Diffusion Magnetic Resonance Imaging methods
Deep Learning
Urinary Bladder Neoplasms diagnostic imaging
Urinary Bladder Neoplasms pathology
Magnetic Resonance Imaging methods
Subjects
Details
- Language :
- English
- ISSN :
- 2366-0058
- Volume :
- 49
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Abdominal radiology (New York)
- Publication Type :
- Academic Journal
- Accession number :
- 38652125
- Full Text :
- https://doi.org/10.1007/s00261-024-04280-1